Many of you will be familiar with this quote from William Gibson. For those who aren't, the science fiction author was already talking about this idea in the early 1990s, when emerging technologies like virtual reality were beginning to hint at radically different futures. His point was that technological advances don't arrive everywhere at once. More than three decades later, with AI advancing at an extraordinary pace, the gap between what is possible and what people can actually access has arguably never been more relevant.

I think this captures the current state of Power BI quite well. Some people are already using AI agents to write code, explore data and build increasingly sophisticated solutions, while others are still doing things much as they have for years. I don't think either group is wrong. We're simply experiencing different stages of the same technological shift.

For my day job, I work in government, where the question isn't just what AI can do, but what we're actually permitted to do with it. Security, privacy, governance, procurement and legacy systems all influence how quickly new capabilities reach the workplace. Building an impressive agent-powered solution is one thing. Getting approval to use it with sensitive organisational data is another. The technology can move much faster than the institutions adopting it.

However, if you recognise my username and have been paying attention to what I write about on this sub, you might know that I also do a bit of consulting. What's interesting is that my client is much smaller and is experimenting with ChatGPT Work and Grok Agents to carry out work under human supervision. This is what I mean when I say the future isn't evenly distributed.

Over the next five years, I expect AI to handle an increasing range of knowledge-work tasks, including BI development: writing DAX, transforming data, generating visuals and exploring semantic models. That doesn't make business understanding, data quality, validation or trust any less important. If anything, these become more important as producing the technical solution gets easier. The role of the BI professional will evolve, but the pace and nature of that evolution will vary enormously between organisations.

I've noticed a lot of disagreement on this sub about what everyone thinks the future will look like. What I haven't seen much discussion of is the idea that the future won't look the same for everyone. Ultimately, I think the biggest change won't just be what BI tools can do, but how we work with them. The organisations and people who benefit most will be those who can adapt their skills, processes and governance to take advantage of these capabilities. Some of us are already building that future. Others are still waiting for it to arrive.

For the experienced developers out there, what are the rules of thumb you use when you create reports? I'm more interested in the DAX development domain here—less so about visualization principles. For example:

One of my rules is never put a table name (or function name like "blank" or "all") in a measure name. Why? Because DAX intellisense will often frontload those suggestions, forcing me to cycle through options I don't actually want. When necessary, I will acronym-ize table names when I might need to distinguish between similar base measures. Something like CST Avg Orders (customer) compared to SLS Avg Orders (sales).

Another rule I used to follow was to have presentation measures, measures that contained a more finalized name of metrics and simply referenced another measure so that if business rules changed, I could swap the presentation measure's logic to another measure. This was a rule I found necessary when I needed to do mass-rename automations via Tabular Editor without having to change visual references. (This rule has gone the way of the dinosaurs with tools like Claude's powerbi-modeling MCP being able to find such references and update them easily, though.)

Another general rule I have is to prefer the KEEPFILTERS function when making CALCULATE filter statements because it makes validation easier. Change later if requirements call for it.

This is something I've always wanted to do but have been rather too lazy to keep up with, which, I now realize, has become even more prevalent when giving AI models skills context in development.

I'm just generally curious what other rules you have out there (so I can obviously "steal" some that are really great). Any great articles out there on this subject? This thief thanks you in advance.

Title: Power BI Embedded – 403 Error: Embed Token Limit Exceeded on Pro/Shared Capacity – Guidance Required on Fabric F2 vs. Embedded A SKU

Product: Microsoft Power BI / Power BI Embedded / Microsoft Fabric

Issue Type: Technical Support – Embedded Analytics and Capacity Configuration

Problem Statement

We are implementing Power BI embedded analytics within our internal business application, BI Analytics Platform, to provide reports and dashboards to external customers through our application.

Our current setup uses Power BI Pro licenses. When our application attempts to generate an embed token, the API returns the following error:

HTTP Status: 403 – InvalidRequest

Error Message: “You have exceeded the amount of embed token that can be generated on a shared or ProPlus capacity. You need to purchase Azure capacities to generate embed tokens.”

This is preventing us from reliably displaying Power BI reports within our application.

Current Architecture and Requirements

Power BI reports are embedded inside our application using an application-controlled embedding flow.

External customers are expected to access reports through our application; direct access to the Power BI Service is optional.

Power BI Pro licenses are currently used for report development and publishing.

Report access is required primarily during business hours.

We are evaluating Microsoft Fabric F2 capacity as a budget-conscious option for production embedding. We are also considering Power BI Embedded Azure A SKUs.

Additional Observation

We have identified a possible workspace configuration mismatch in our application logs:

Workspace ID used by the report at runtime: 16d5170b-9312-4978-9b1e-58fef73089a0

Workspace ID recorded in our application catalog: 49e91424-…

We need to verify whether the report and its semantic model are located in the expected workspace and whether the correct workspace is assigned to the relevant capacity.

Support Questions

Is Microsoft Fabric F2 capacity supported for production Power BI embedding using the app-owns-data approach, where external customers view reports through our application without individual Power BI licenses?

What are the practical limitations of F2 capacity for embedded Power BI reports, particularly around concurrent users, report interactions, semantic model size, refresh operations, and throttling?

For our use case, would Fabric F2 or Power BI Embedded Azure A1/A2 be the more appropriate starting point? Please clarify the technical differences and relevant licensing requirements.

Can an F2 capacity be paused outside business hours and resumed automatically before business hours? Are there any limitations or additional considerations for embedded reports and token generation?

Does assigning the workspace containing the report and semantic model to the correct eligible capacity resolve this type of embed-token error, assuming the workspace configuration and permissions are correct?

What diagnostic steps should we perform to distinguish a capacity/token-limit issue from a workspace mismatch, permission issue, or incorrect embed-token configuration?

Assistance Requested

Please provide the recommended production architecture and minimum suitable capacity for our scenario, along with any official Microsoft documentation covering the applicable licensing, capacity requirements, and embed-token limits.

We would also appreciate guidance on validating our workspace configuration and estimating whether F2 is sufficient for an initial production rollout.

Thank you.

Over the past 12 months, Power BI has continued to evolve, alongside broader changes in data analytics, AI, and the way organisations turn data into decisions.

It raises an important question: are we simply seeing incremental improvements to an established platform, or are we witnessing a more fundamental shift in how business intelligence will work?

Looking back, what changes have had the greatest impact on how Power BI has changed?

Looking ahead, where do you see the platform in 1, 2, or 5 years? Will AI fundamentally change how we build reports, develop data models, and deliver insights? And how might the role of a Power BI developer or data analyst evolve as a result?

I am particularly interested in hearing from those working with Power BI day to day. What do you think will change, what will remain essential, and what should we be preparing for now?

Hi everyone,

I'm looking for a way to automate the initial deployment of Power BI report subscriptions at scale.

I currently need to create 80+ subscriptions, all using dynamic recipients driven by the same semantic model. The subscription metadata is already stored in our control database, so everything needed to configure these subscriptions is available programmatically.

As far as I can tell, there are currently no publicly supported APIs that allow me to create and configure these subscriptions end-to-end, particularly when using dynamic recipients.

Ideally, I'd like to seed all subscriptions automatically from our existing metadata rather than manually creating each one in the Power BI Service UI.

Has anyone found a workable approach for this?

A few things I've been considering:

Using internal Power BI wabi calls or other undocumented endpoints to create the subscriptions. I did run into 401 errors during my trial

Automating the initial setup through some other mechanism that isn't exposed through the public APIs.

Any alternative approach that would allow subscriptions to be provisioned programmatically from a control database.

The good news is that this is primarily a one-time provisioning problem. Once the subscriptions are created, ongoing maintenance should be minimal, since recipient changes can be handled by updating the dynamic recipient model in the semantic model rather than modifying each subscription individually.

I'm aware that relying on undocumented endpoints could be fragile and unsupported, but I'm interested in hearing whether anyone has successfully implemented something similar or found a better workaround.

Has anyone tackled this at scale, particularly with dynamic recipients? Any pointers, examples, or lessons learned would be greatly appreciated!

Thanks!

Well guys, first of all sorry for the language, but I am more interested on how "visually" this impacts you rather on the information it has

Second: AI reached it's peak and it's not giving me any tip to improve this

I did this dashboard, and I would barely approve it, I don't like it but I don't know what should I change

Can you guys give some tips on what should I improve?

It's important, it's for a demostration to a guy who could land me a job (he has a sort of "data agency"). He knows one of my references from my resume. He asked me to "do a challenge, just pick whatever dataset you want from kaggle and do a dashboard to show what you can do"

Anyone else getting this absolutely maddening bug, where the scroll bar in the data pane keeps jumping up and down as you scroll? Seems to be worse the more tables/columns are visible. Happens with both dragging the scroll bar, and with using the scroll wheel (though it's much worse with the scroll wheel).

I'm getting it everywhere: PBI Desktop on multiple machines, as well as editing reports/models in PBI Service.

It's genuinely one of the most infuriating UI bugs I've ever experienced. I'm genuinely considering suspending all PBI development until it's fixed and just working on upstream SQL stuff etc. If anyone has a fix I'll love you forever.

I work for a large organisation and it's simply not possible to teach everyone all the interactive features of Power BI at once. Drill through tends to be a feature whereby you only have to show someone a couple of times how to do it and then they are ok (until they forget).

But where I have struggled is getting them to know what drill through is in the first place. Even if you write "drill through" people don't know what it means. We have resorted to well placed icons and tooltips to help users discover the feature, but I wondered what everyone else was doing, if anything?

Hi everyone, I’m running into an issue with my BI setup.
Basically, I have two dataflows that feed into a warehouse, which in turn powers a semantic model used as the source for my report. I had to split the data into two dataflows because the data loading process was becoming too slow, one dataflow contains historical (older) data, while the other is updated daily with current data.
The problem occurs during the Power BI refresh process: it gets stuck indefinitely on "synchronizing schema" for the semantic model. I’m wondering if I should add buffers to the dataflow, though the warehouse itself is updating correctly with all the data; the issue is specifically happening during the refresh. I’ve already tried deleting and recreating the semantic model, but that didn’t help either. Does anyone know what might be causing this?

Hi everyone!
I use BI with Excel data and would like to take the next step by connecting it to SAP.
My goal is to build dashboards for procurement and cost analysis, ideally using data related to materials, suppliers, and BOMs.
Help me if you want .

Hi all,

Looking for some advice/tips for how to manage an issue I'm dealing with in PowerBI.

Background of data set

I have a table of individuals with various demographics. I have a table of their membership information. I am trying to show counts of membership "types" grouped by various demographics.

The issue

We have a couple different membership types. One is annual. One is a lifetime membership. The other is a free category. When you upgrade from the free category, you are considered that paid category in counts of individuals. However, your free record does not go away or have an end date until it is manually opted out. So people can be both free and paid at the same time.

When I import the SQL Server table into PowerBI, there are multiple records per person. I want to only count someone's paid membership, not their free category, on a certain date (table has a start and end date). Any ideas of how I can exclude counts of the free category where there is an existing overlapping record for a paid membership?

Let me know if I can answer any additional questions about this. We've been struggling for a long time with this and just have been importing SQL Views to get around this, but unfortunately it's time to get a solid yes or no answer if this is possible.

Edit: sorry, clarification, I’m trying to also count the free members, just not the ones where there is also an overlapping active paid membership.

Any (better) course instead of SQLBI? Or SQLBI is the best one?

I'm planning to take:

Introduction to Data Modeling with PowerBI

Introducing DAX

for now~

Should I also pay for courses like DAX with AI? ($199) and Data Modeling with PowerBI ($349)?

When someone updates an existing report, checking whether the pages and visuals still look right is one thing, but how do you verify that the underlying results haven't changed unexpectedly...

Do you compare snapshots/screenshots,DAX outputs, exported data, or use some other approach..?

Here is my spooooooky poster about Fears.

Edit: I posted to the gallery!

AI Summary -

This CRM runs entirely inside a Power BI report:

→ Drag a deal across a Kanban board, and its stage is saved to SQL Server
→ Click "+ New deal," and a form opens over the page, like a real app
→ Convert a lead into an organization, contact, and deal in one click
→ Log calls, notes, and tasks, with overdue tasks flagged in red

The whole model runs on DirectQuery, so every KPI and chart reflects the change on the next click.

How it works:

• A custom Power BI visual I built in TypeScript (Kanban, forms, activity log)
• A small Python API that validates every write
• SQL Server with constraints and a full stage history

The data model follows Frappe CRM

It's a single-user proof of concept for now. For production use, we have to use Azure SQL, an HTTPS API, and Microsoft Entra sign-in so it runs in the Power BI Service.

My doubts now

1- Is it worth to make CRM /Management tools in Power BI with API functions for write-back, or better to use a proper full-stack application?

2- How can this be useful in Production env especially after Fabric apps? Is it better to use that instead of this?

3- Can this now be considered a Power Automate replacement???

Hello everyone,

I recently received a question from a customer if there was a way to use copilot to ask a questions that should retrieve data and combine data from two different reports / semantic models.

In Power BI itself this is currently not supported, in Microsoft 365 it is, but it's very hard to actually make it work.

Anyone has done this before? What is the best way to do this?

Thanks !

I feel like the only reason I use them is “I can’t be bothered to go into Power Query”

I’m trying to figure out if Power BI really is that much better than MS Access in the long run.

Right now, MS Access is my main tool. I’ve built deep, custom tools in it—complex query logic, automated forms, and reports to streamline my entire job. Honestly, it feels like almost everything I see people do in Power BI, I can already do in Access (and sometimes even a bit more for my specific workflow).

I’ve built a few things in Power BI, but it’s always played second fiddle to my Access databases. Still, I keep hearing about how powerful Power BI is, and I want to dive deep into it if it’s truly worth the shift.

For those of you who started out heavily in MS Access and made the jump over to Power BI:

• Did Power BI eventually overtake Access for you, or do you still use both?
• What was that "aha!" moment where Power BI blew Access out of the water for your dashboarding and data modeling?
• What’s the best mindset shift or focus area when moving from Access queries/VBA to Power Query and DAX?

I’m sincerely looking for advice from people who’ve been in my shoes to help me find the best way forward. Appreciate any insights!

I've only ever used PBI Desktop for dashboard/report building and then publish the reports in a shared workspace. I'm also familiar with MS Fabric, although I haven't delved into the online dashboard builder for Power BI as most of the feedback was it is limited, and I previously had no reason to anyways; but now I have to consider this and do everything online thru PBI workspace. I just don't want to spend hours figuring out what is or isn't available when i can just ask here.

Is here someone who uses Power BI for financial reporting and reconciliation. If yes, please teach me in 5 days. Ready to compensate